Author: Michael Schrage

Transformationally speaking, technological innovation is easy. Culture change is not. Jeff Bezos knows this. If he wants to kindle his newly-acquired Washington Post into Amazon Prime, he’s free to do so. Technically enhancing the Post will be a digital snap. Getting his paper — pun intended — to adopt, adapt to or embrace an authentically customer-centric Bezosian vision, however, will prove very, very hard.

The reasons for that resistance will have little to do with money but almost everything to do with the Post‘s proud, defiantly elitist and self-righteously professional self-image (a self-image equally ensconced in papers like The New York Times, The Boston Globe and Los Angeles Times, as well). That prideful culture is simultaneously responsible for the paper’s greatest successes and most humiliating journalistic and commercial failures.

As a former reporter and columnist there, I genuinely admired and respected both my newsroom colleagues and our business counterparts. But the Post’s brave new entrepreneurial owner undeniably embodies two values that were never part of the paper’s cultural norms: (1) being data-driven and (2) providing measurably superior customer experience. That’s simply not what newspapers do.

Almost everything that makes Jeff Bezos Jeff Bezos as an innovator is organizationally alien to what made The Washington Post The Washington Post as a newspaper. At the Post, reporters report, editors edit and ad sales people sell ads. Journalists tell stories and report news; they don’t do UX. Newspapers are indeed in information and digital content businesses. But their decision-making is typically far less data-driven than the big box retailers whose advertising they’re so desperate to get. As a rule, newspapers know less about their readers and advertisers than an Amazon, Google or Facebook does.

These institutions built their brands not by focusing on customer experience or using strategic analytics but by successfully defining the most important and newsworthy stories in their communities and beyond. Those days are officially gone. So are the business models that made them profitable. The competition has both bigger and better data while offering much better customer experiences. There’s little these papers do that deserves to command a marketplace premium from customers.

Serious innovators look to Amazon, not The Washington Post, The New York Times, The Wall Street Journal or The Boston Globe for innovation inspiration. Being a better newspaper or having better reporters, editors, web masters and ad salespeople doesn’t solve the problem. They’re no longer fit for purpose. The whole is worth less than the sum of its diminishing parts.

So when Bezos writes, “We will need to invent, which means we will need to experiment. Our touchstone will be readers, understanding what they care about — government, local leaders, restaurant openings, scout troops, businesses, charities, governors, sports — and working backwards from there. I’m excited and optimistic about the opportunity for invention,” he effectively acknowledges that the status quo he purchased is unsustainable and — more importantly — existing cultural norms cannot endure. Can elite — and elitist — journalists who professionally prefer to tell readers what’s important reinvent themselves as interlocutors and explainers who can digitally engage to inform? Will editors who’ve learned how to motivate prima donna reporters be able to turn themselves into “crowdsourcing shepherds” capable of tapping the collective intelligence of reader communities into stories everyone tweets, links to and talks about? Can people who went into publishing precisely because there was no math learn how to take statistical advantage of petabytes of data to better customize, personalize or illuminate a customer app or experience? Will an industry that has institutionally treated customer feedback as an irritant — look at the online comments section of any major newspaper — finally have the wit and innovation to monetize their readers’ best, brightest and most provocative comments?

The answers, as Bezos surely knows, have little to do with the Post’s technical abilities to interoperate with Amazon Web Services and everything to do with profound cultural transformation. You can’t lead at Amazon unless you’re willing to be data-driven and relentlessly invested in improving customer experience. Will that Bezosian ethos be true for the Post in three or four years? Or will Amazon’s founder be demonized and dismissed as someone who “just doesn’t get” what elite journalism is supposed to mean?

These cultural challenges aren’t unique to the Post; they’re endemic to the industry. Nate Silver, arguably the most innovative data-driven journo-blogger in America, recently left The New York Times for ESPN. John Henry, the billionaire investor who brought Bill James and “Moneyball” insight to the Boston Red Sox — and winning the World Series in the process — just purchased The Boston Globe from The New York Times Company. Could a Bill James/Moneyball approach transform newsroom culture and best practice much the way it did for baseball? Of course. Then again, there’s already a Bill James/Moneyball innovator in the daily news business; it’s called Google. Bezos knows about competing with them, too.

For now, Bezos is keeping the current leadership of the Post in place. The Washington Post I know was a “lead by example” place. What data-driven decision and customer experience leadership examples will they now set? What do they want to learn from their new owner to help transform their old newspaper? How will they reinvent themselves?

Because if the paper’s leaders don’t embrace and enact Bezos’ values, you can be sure the newsroom won’t either. That would truly be the end.

Talk about turning a bug into a feature. SAP, the German software giant, announced that it hopes to hire hundreds of autistics as talented programmers and product testers. The firm told the BBC that by 2020 perhaps 1% of its global workforce of 65,000 would be people with autism. Though a medically recognized DSM-5 disorder, many diagnosed autistics apparently bring special cognitive flair to digital details and computational concentration.

“We share a common belief that innovation comes from the edges,” said Luisa Delgado, an SAP HR director, who noted the company valued the ability of many autistic people to “think differently and spark innovation.” SAP’s Bangalore office saw its productivity increase after deploying autistic hires. The company is working closely with a Danish not-for-profit specializing in IT job placements for individuals with autism spectrum disorders.

Special talents with serious personality disorders aren’t rare. While not autistic, the late Steve Jobs was described by many who knew and worked with him as classically in the grip of obsessive compulsive personality disorder (OCPD). In Joshua Kendall’s book, America’s Obsessives, the DSM defines the condition as “a preoccupation with orderliness …and mental and interpersonal control” and lists eight symptoms, at least four of which are necessary to reach a diagnosis. These include perfectionism; preoccupation with details, rules, orders, lists, organizations or schedules; excess devotion to work; inflexibility about matters of morality, ethics or values; reluctance to delegate tasks unless others submit to exactly his way of doing things; and rigidity and stubbornness.

Does this describe any of your better colleagues, clients and/or employees?

The thrust of Kendall’s thesis — which also profiles such innovative obsessives as cosmetics’ Estee Lauder, ketchup’s Henry Heinz and aviation’s Charles Lindbergh — is that such disorders are frequently inherent for relentless overachievers.

But the undeniable success of individuals and entrepreneurs with disabilities and personality disorders raises disturbing questions. Helping determine their professional development and best interests becomes a welter of conflicting interests.

What happens as medicines and therapies for autistics improve? If drugs and/or medical intervention effectively treat the awkwardness and dysfunction associated with autism, might they also undermine the cognitive skills and abilities that originally got those autistics hired by SAP and other IT firms? Would autistics feel compelled to cling to their disabilities for fear of losing their jobs? Would organizations be reluctant to encourage these employees to seek treatment because that hurt their performance and productivity? Ironically, a cure for autism likely obliterates the disorder’s competitive advantage in the global marketplace.

Similarly, if Atari’s Nolan Bushnell had recognized the young Steve Jobs’ OCPD and insisted his highly talented technician get the counseling and pharmaceuticals he needed to be a healthier person, would there have even been an Apple Computer, let alone an iPhone and iPad? Well-intentioned top management interventions — sincere efforts to help produce an better balanced employee — might have snuffed out the entrepreneurial essence that made Jobs one of the world’s greatest innovators. The unavoidable ethical — and practical — business dilemma is whether it makes sense to “improve’” employees whose effectiveness may be contingent upon their disabilities, dysfunctions and pathologies. What does “professional development” mean if it runs the real risk of making a colleague or employee less valuable to the enterprise?

If high-performers get measurable workplace results because — not in spite — of their disorders, the kinds of “professional development” investments that make sense and add value seem ethically and pragmatically unclear. There is a real risk that the cure could be worse than the disease.

I see no happy resolution to these conflicts. For truly talented high performers, achieving “balance” may prove a self-destructive myth. They need their dysfunctions and disabilities to succeed. But is it honorable, ethical and even legal to hire people knowing that making them better as a person may make them less valuable as an employee? I don’t know. It will be fascinating to see how SAP’s talented recruits are promoted inside their organization and out.

In an impressively short time, Kickstarter has quickly become the go-to high-impact mashup of crowdsourcing sensibility and entrepreneurial endeavor. If you’ve got a genuinely creative idea — or even a “me, too with a twist” — Kickstarter’s “crowd funding” platform offers a genuinely innovative way to finance creativity and innovation. Since its 2009 launch, Kickstarter claims that more than 4.1 million people have pledged over $619 million to fund over 41,000 projects. It’s exciting.

But Kickstarter’s inspiration and effectiveness at facilitating “just-in-time creative communities” — or what has also been described as “impulse patronage” — poses a provocative challenge to the C-suites of global organizations worldwide: Where are their Kickstarters? Why aren’t leaders tapping the crowdfunding capabilities of their own innovation ecosystems to stimulate their people and ideas?

The Kickstarter model should be a part of the innovation infrastructure of every global enterprise that takes intrapreneurial creativity and coherent corporate culture seriously.

Internal venture capital and skunk work projects are nothing new. Corporate behemoths — like IBM and its innovation jams, 3M’s open innovation efforts and Procter &Gamble’s connect + develop programs — are constantly looking for ways to cost-effectively leverage their scale while safely exploring potential innovation opportunities. Many of these initiatives enjoy some success; most do not.

But one inherent challenge — flaw? — in the overwhelming majority of the innovation initiatives I’ve seen is how intrinsically compartmentalized, segregated and silo-ized they become. They’re creative and/or innovative efforts appealing to creatives and innovators. They’re not designed to appeal to the organization — let alone its ecosystem! — at large.

Moreover, funding for innovation overwhelmingly comes from “budgets” rather than any discretionary funds held by individuals or small teams. “Impulse patronage” looks and feels like impossibility to anyone who isn’t a manager with a cash-flow-positive P&L and the courage to take a chance. The idea that employees could contribute their own money to help kickstart a provocative proposal is organizational heresy. Perhaps it should be. But what if a slice or sliver of people’s compensation was denominated for Kickstarter-esque discretionary financing? Why not make the organization a marketplace that creates the option to tap not “the wisdom of crowds” but the “excitement of employees” or the “perceptions of personnel”?

Virtually every global enterprise of note, whether commercial or non-profit, now has the internal networks and social media tools that make internalizing a Kickstarter-like initiative technically possible. The more obvious, and challenging, concern is whether organizational leaderships have even begun to think through the innovation implications of these novel tools, technologies and techniques for creating new coalitions of creative intrapreneurs and empowered individual investors. I’d say not.

But let me steal Kickstarter’s advice to artists and entrepreneurs who want to use its platform to elicit funding and support: “Audiences respond to passion, sincerity, and an ability to execute. They want to see you communicate this in your video, and they want you to offer creative rewards that are fairly priced.”

How difficult or culturally incompatible would translating that call to action be for most global enterprises?

Put another way, what CEO, CMO or innovation leader wouldn’t want to learn what kind new products, services, user experiences, etc. their individual employees would be willing to fund? What a fascinating — and fantastic — way to take the innovation temperature of the enterprise. What kinds of proposals would lead to regional and functional oversubscription? What kinds of projects never get funded?

Kickstarterizing the enterprise provides a powerful way of rebalancing top down innovation efforts with bottom/middle up projects that inspire cross-functional/trans-border support. If you’re a P&G, a Toyota, a General Electric or a Haier, this is exactly the kind of innovation marketplace you need to be testing not just to get new ideas but to see what gets your people from all over the world interested and excited enough to invest. That is, to me, a large part of what healthy innovation cultures are all about.

Wouldn’t it be a kick-in-the-head if the most innovative and creative efforts Kickstarter inspired were its effective emulation by the world’s most innovative organizations?

Unhappily shocked by Sputnik’s unexpected 1957 success, President Eisenhower quickly pushed the Pentagon to establish the Defense Advanced Research Projects Agency (DARPA). Its ostensible mission: “to prevent technological surprise to the U.S. military, and to create surprises of its own.”

Anticipating and enabling “technological surprise” has become even more challenging, DARPA director Arati Prabhakar recently told an MIT audience, because more people in more places have more access to more technology that ever before. Surprises can come from anywhere. In an era of greater global trade, knowledge transfer and transparency, Prabhakar unsurprisingly reports DARPA’s core value proposition demands disproportionately greater imagination and ingenuity. Predictability breeds complacency. Predictability is DARPA’s cultural, technical and organizational enemy.

The more Prabhakar talked, the clearer it became that DARPA’s intimate historical relationship with surprise offered a powerful conceptual model for serious innovators worldwide. What role should surprise play in defining one’s innovation brand in the minds of customers and competitors? To surprise or not to surprise? That is the innovation question. (This question from a marketing perspective was recently explored on this site.)

For Apple, the iPhone and iPad were unquestionably strategic surprises explicitly intended to disrupt established industries and disorient entrenched competitors. Steve Jobs, who had always sought to surround his company in auras of mystery and secrecy, was a master of injecting the unexpected into the zeitgeist. Indeed, Apple assiduously cultivated “expect the [delightfully] unexpected” as part of its innovation brand.

While seen neither as flashy nor as glamorous as Apple’s offering, Amazon’s Kindle and Fire platforms similarly signaled strategic surprise. Jeff Bezos transformed perceptions surrounding Amazon as a global retailer by making clear they wanted to be a global innovation ecosystem as well. Amazon had made itself accessibly and invitingly unpredictable.

After initially dismissing tablets as inferior to laptops, Microsoft surprised a number of its partners and developers by introducing Surface. A defensive surprise, to be sure, but one acknowledging Microsoft’s competitive environment had completely changed.

But the greatest determinant of effective innovative surprise is not technical capability — it’s expectations.

Surprise is about expectations. Successful surprises subvert, destroy and/or exceed expectations. The great innovation tension in business is appropriately managing expectations. With apologies to Clay Christensen, this other “innovator’s dilemma” asks, “Is it better to be ‘predictably surprising’ or ‘surprisingly predictable’?” That is, do customers and clients prefer the comforts of predictable improvements and enhancements that fall squarely within educated expectations? Or would they rather the thrill and novelty of innovations that challenge and intrigue them in unexpected ways?

If you’re an Apple or a Samsung or an Amazon, is your brand better off building expectations around “no surprises” innovations that happily soak your customers in the warm bath of familiarity? Or do you gain greater brand equity by creatively disrupting the very expectations they’re predisposed to bring to your products and services?

The simple thought-experiment and test I advise innovators to explore is substituting the phrase “pleasant surprise” for “innovation” whenever they discuss new offerings and upgrades. There’s a world of UX difference between a significant innovation and a significant pleasant surprise. In fact, as many innovators discover to their sorrow, many of their most innovative features and functions are frequently regarded as unpleasant surprises.

How intimately do your designers and marketers link and measure the value of an innovation to the pleasure of its surprise? The great paradox, of course, is that the more people expect surprises, the less surprising those surprises are.

And surprise, like any other differentiator, can quickly hit diminishing returns. But, as DARPA’s successful history as a surprise-based innovator suggests, understanding the differences and distinctions between “proactive” surprise and “reactive” surprise can pay huge dividends. What’s surprising is how few innovators appreciate that.

The most useful question I’ve learned to ask people about analytics is, “What do you plan to do with them?” By far the most interesting answer I’ve gotten comes from basketball superstar LeBron James: Hire Hakeem Olajuwon.

Until his championship 2011-2012 season, NBA cognoscenti viewed James as a phenomenally gifted loser. He could do everything but win when it mattered most. No one doubted his desire or ability, but they demonstrably weren’t enough. You don’t have to care about sports to realize that exceptional talent, dedication, discipline, teamwork, and hard work assure neither improvement nor victory. You also need self-awareness and smarts.

What do you need to know and emulate about LeBron James’ journey to championship level?

No, you can’t hire Hakeem Olajuwon. But you can look at “The Evolution of King James.”

Kirk Goldsberry brilliantly describes the open secret to James’ success: Nothing makes serious competitors more open to analytics than losing. A basketball genius frustrated with his professional failings decided he wasn’t as good or as smart as he needed to be. James took a good hard look at the analytics (which Goldsberry brilliantly and visually illustrates) and an even better and harder look at himself. Then he hired retired NBA legend Olajuwon — the only player in NBA history to win the MVP, Finals MVP, and Defensive Player of the Year awards in the same season — to help remedy the analytically undeniable flaws and shortcomings of his game. He explicitly linked analytics to his personal/professional transformation.

“I wanted to get better,” James said of his decision to work with Olajuwon. “I wanted to improve and I sought out someone who I thought was one of the greatest low-post players to ever play this game. I was grateful and happy that he welcomed me with open arms; I was able to go down to Houston for four and a half days; I worked out twice a day; he taught me a lot about the low post and being able to gain an advantage on your opponent. I used that the rest of the off-season, when I went back to my hometown. Every day in the gym I worked on one thing or I worked on two things and tried to improve each and every day.”

And there’s more to the story. The workouts were scheduled to begin each day at 9 a.m. While Olajuwon did show up regularly on time, James always was already there, sometimes having arrived by 8:20.

“He would be there stretched and ready to go,” Olajuwon said. “That says a lot about him and his determination. I was impressed that he couldn’t wait to get started.”

“I went there to put in work,” James said. “That’s what it’s all about. I didn’t want to do anything else but to get better.”

Not incidentally, James brought his own videographer to record the sessions for later study and review. The Olajuwon sessions were not just “classes” or “workshops” or “training sessions” — they were the continuation of a transformation process rooted in the analytics. The true test of analytics isn’t just on how good they are but in how committed you are to using them to improve. Of course, James didn’t just make a commitment; he got one from Olajuwon. Those commitments unambiguously paid off last year.

The results thus far speak for themselves this year, as well. Self-improvement in teams requires teams.

Most people reading Harvard Business Review aren’t as talented in their field as James is in his. But how many of us have committed to measurable self-improvement based on analytic insight? How many of us have hired the right coach for the right reason?

Many readers were irritated by an earlier post describing how predictive analytics would increasingly determine who companies would hire, fire, and promote. Data-driven decision-making about people and their potential seem to be the digital destiny of human capital management. But this argument leaves out a crucial variable.

The surest way to disrupt the quantitative tyranny of predictive analytics is demonstrable self-improvement. Individuals and organizations alike have to move away from the notion of analytics as the key to insight and towards the belief that they’re the GPS of transformation. Self-improvement, not self-knowledge, is the goal.

Have you had an analytic epiphany? Good. Now ask yourself: Who is your Hakeem Olajuwon?

Future potential matters (much) more than past performance. That’s the new quantitative consensus reshaping professional sports worldwide. After looking hard at the numbers and algorithms, the smartest — and richest — general managers and franchises have made up their collective minds: They’re not paying a premium for yesterday. Period. Iconic athletes from Barcelona to Manchester United to the Chicago Bears to the New England Patriots to the New York Yankees have been effectively cut loose.

Thanks for the memories. See you at the Hall of Fame induction ceremonies, dude. We simply can’t — or won’t — afford you anymore.

Multivariate predictive analytics render “What have you done for me lately?” an anachronistic cliché. The questions now are, “How well will you do tomorrow?” and “How can we be sure?” The better the answers, the richer the paychecks. The past is, indeed, a foreign country, albeit one with a debauched currency. This next-generation “moneyball” ethos now transforming pro sports has enormous implications for how high-performance managers will incent and inspire tomorrow’s high achievers. The cultural values of loyalty and leadership are being redefined by the economic value of forecasting methodologies (PDF). “Yesterday” is a sunk cost.

“Yes, the trend is towards paying for future performance; by that I mean future ‘forecasted’ performance,” observed Daryl Morey, General Manager of the NBA’s Houston Rockets franchise and a pioneer in bringing moneyball statistical/quantitative analytics to pro basketball, in a conversation with me. “My job is to up our odds for winning games and winning championships, and those things happen going forward, not looking backward.”

Exactly. Where past performance was once the best and most reliable proxy for the future, says Morey (a friend who launched MIT’s successful Sports Analytics Conference), algorithmic and biomedical innovations increasingly give coaches, managers, and owners greater confidence in predicting which players have peaked and which ones will step up to greatness. “We have a luxury in sports,” says Morey. “We can so clearly measure success and failure; we can know when people start fading with age…we can make a better bet on someone with talent.”

Unlike for a Procter & Gamble or Unilever, Morey muses, there is no “aging curve” for marketing prowess: “We can’t say that, after 50, this guy won’t have another good marketing idea again.”

But why not? If you’re running Procter & Gamble, Unilever, Google, Exxon Mobil, or Ford, you have comparable concerns about making sure you’re getting the best possible returns from your talent and human capital investments. You should be concerned about the aging curves of your marketing people; you should want to know if your tech support folks will deliver better outcomes tomorrow than today; you should be predicting which sales teams will procure the most lucrative contracts with the minimum risks. Think of it as Six Sigma predictive analytics for talent.

The catch, which Morey freely acknowledges, is that it’s still very difficult to measure what role personal loyalty plays in inspiring extra efforts that yield better results. It’s still very difficult to assess the positive influence of an aging leader whose physical skills have demonstrably diminished but whose acuity and character gets everyone on the team to step up their game. No one denies the reality or importance of these organizational phenomena. But that’s not the direction that moneyball’s metrics have been going.

“All of my actions have to be on the individual level,” Morey acknowledges, while freely conceding that oftentimes a team’s greatest professional challenge is chemistry and cohesion. Of course, encouraging the kind of loyalties and leadership that enhance collaboration becomes inherently more difficult when performers fear they may fall on the wrong side of the aging curve. Similarly, coaches lose credibility with their players if they champion schemes and approaches that predictive analytics might undervalue or ignore come contract time.

The classic response, of course, is to insist that, ultimately, these decisions come down to human judgments rather than computational dictatorships. But that’s exactly why acknowledging the current trend is so important: The leaderships of the richest and (ostensibly) best-managed franchises in sports have effectively declared that the costs of preserving past values are too high relative to the potential for tomorrow’s performance.

Bill Parcells, the Super Bowl-winning coach, was famous for saying, “You are what your record says you are.” Today, that’s no longer true. You are what the analytics predict you will be. That changes the social — as well as the professional — contract.

Does anyone really think a 50-year-old marketer with a terrific track record is immune from the same economic and analytic forces affecting the career of a 40-year-old pro athlete who was a two-time all-star? Does that knowledge make the marketer a better leader or more loyal employee? Or doesn’t that matter anymore?

Do you know where you are on the aging curve? Does your boss?

“A picture is worth a thousand words” may be a lovely cliché, but it’s exactly the wrong way to view visualization. As admirable as the craft, message, and data-driven artistry of the Edward Tuftes and Stephen Fews may be, successful visualization is less about effectively conveying complex information than creatively provoking human interaction.

Infographics should (quite literally) be seen more as interfaces to interpersonal engagement than aesthetically pleasing packages of numbers and analytics. The essential question smart “visualization” and “visualizers” should address is not, “What’s the best and most accessible way of presenting the data?” but “What kinds of conversation and interaction should our visualization evoke?”

Visualization works best when generating situational awareness and contexts that otherwise wouldn’t exist. Like the best maps and GPS, they simultaneously provide a sense of where you are and insight into where you might want to go next. Individual epiphany defers to interpersonal interaction: Is this where we really are? Given what we see here, do we really want to go there? Visualizations support and enhance teams and teamwork.

So I cannot overstress the power and importance of visualizations as portals. I will never forget an Excel-enabled experience almost 20 years ago when a presenter toggled from histograms to pie charts to cells to macros to the raw data tables in a product performance review. Visualizations weren’t static summaries; they were digitally dynamic gateways into more detailed data (and the statistics manipulating them). The visualizations synthesized, but not at the price and cost of denying deeper and more granular views.

The resulting conversations were, of course, immeasurably enriched by this approach. Questions and disagreements could be addressed at whatever layer — or layers — of visual representation was most fit for the purpose. The multiple visualizations were integrated, interoperable, and inspiring. They effectively facilitated a collaborative interaction that would otherwise not have been possible.

More recently, the Consortium for Advanced Simulation of Light Water Reactors (CASL) visualizations had a huge impact on an innovation workshop because they facilitated a cross-functional design conversation that the organization’s existing visualization portfolio could not. Why? Because the firm’s simulations were dedicated to modeling known problems instead of inspiring collaborative interaction. The CASL simulations effectively forced the organization to rethink how visualizations could be used as platforms to create common understanding across the enterprise rather than as high-resolution tools to support technical specialists.

I’ve (literally) seen this visualization influence recapitulated in hundreds of other design and innovation environments. Instead of pretty PowerPoints and charismatic keynotes engineered around the ideal of optimizing information presentation, visualization was treated as a compelling invitation to engage and interact with both the material and each other. In other words, visualization was less about presentation than UX — user experience. Visualization was managed as a UX design challenge rather than how best to put on a data-driven show.

Is this unduly harsh or cynical? No. Look at Gardiner Morse’s excellent post on “crap circles” or Dylan Lathrop’s post on peak infographics. The information/presentation design bias taints the overwhelming majority of visualization efforts. That’s both a pity and a problem. Until visualizers embrace the design imperative that their visualizations should be as much about facilitating interaction as conveying information, they’re doomed to be high-resolution underachievers.

Yes, accessibility, understanding, and insight are the wonderful products of wonderful visualizations. But truly transformative visualizations invite people to touch, stroke, and go deeper into the data that underlie them. They engage. They encourage engagement. They give their users a new way to view each other, as well as the data.

Is a picture worth a thousand words? Sure. Maybe even ten — or a hundred! — thousand. But you want to make sure they’re the right words. Don’t view visualization as a medium that substitutes pictures for words but as interfaces to human interactions that create new opportunities for new value creation.

Visualizing Data
An HBR Insight Center

• What Moleskine’s Market Position Really Looks Like
• The Value of a Good Visual: Immediacy
• It’s Time to Retire “Crap Circles”
• We’ve Reached Peak Infographic, and We’re No Smarter for It

Asked several years ago to describe the most important argument taking place at Walmart, then-CEO Lee Scott immediately replied, “The size of our stores.” The world’s largest retailer was debating just how small its footprints and formats could be while still serving customer needs and its own brand equity promise. That conversation, Scott said, provoked a lot of new thinking and analysis.

The most important argument at a fast-growing Web 2.0 services provider revolved around its “freemium” offer. Should the firm aggressively test multiple ways to hybridize its free and fee services? Or would prizing and positioning simplicity above all make the most sense? For a prestigious publisher, the essential — and vociferous — disagreement cut to its entrepreneurial core: Should its popular conferences reinforce the firm’s “countercultural” vibe? Or should they comfortably embrace the world’s biggest, richest, and most established firms, as well?

All firms have strategies and cultures. But sometimes the quickest and surest way to gain valuable insight into their fundamentals is by asking, “What’s the most important argument your organization is having right now?”

The more polite or politically correct might prefer “strategic conversation” over “argument.” But I’ve found the more aggressive framing most helpful in identifying the disagreements that matter most. Of course, there’s frequently more than one “most important argument.” And arguments about which arguments are most important are — sorry — important, as well. (If people insist there are no “most important arguments,” the organization clearly has even bigger unresolved issues.)

The real organizational and cultural insights — and payoffs — come not just from careful listening but recognizing that, as always, actions speak louder than words. What role is leadership playing here? How is the CEO listening to, leading, or facilitating the argument? Is disagreement viewed as dissent? Or is it treated as an opportunity to push for greater clarity and analytical rigor?

Sentiment is as important as situational awareness. Some arguments stir organizational emotions in ways others do not. Similarly, some disagreements energize the enterprise just as surely as others drain the life out of people. Having the same most important argument for years tends to be a very bad sign.

Responses to most important arguments typically fall into one of three rough interrelated categories: strategy, values, or people. Strategic arguments tend to be the most straightforward: Do we compete in this space or not? Are we going to be a leader or not? On the other hand, values arguments are understandably more complex: Does attempting to serve a new customer base compromise who we (think) we are? Do we want to make ourselves even more data-and-analytics-driven in our decision making? Does our intense customer focus risk violating their privacy? Values arguments, even more than strategic disagreements, tend to engage a greater portion of the firm. Healthy arguments around conflicting values demand smart facilitative leaders and leadership at all levels.

Intriguingly, the worst most important arguments I hear usually revolve around people. The CEO or a particularly intrapreneurial business unit leader exhibits behaviors or makes comments that polarize. What did the CEO mean by that? Can you believe the company lets that manager get away with that? What might be called gossip in some organizations mutates into strategic or values arguments. Values and strategic arguments are played out through people and personalities. Corporate characters are alternately heroes, knaves, wizards, and fools. There’s often a fine line between strong and powerful leaders and personality cults. If you think the most important arguments going on in your organization revolve around particular individuals and their unusual mix of style and substance, watch out.

But that affirms one of the great virtues of the question: Are you having the kind of most important argument you want your organization to have? Are you having the right kind of arguments in general? Are your arguments illuminating the path forward or providing the organizations with even better rationalizations and excuses for inaction?

And if you’re not having the right kind of important arguments, then just how much is consensus and alignment really worth?

Who do Yahoo’s “work@home” telecommuting champions think they’re kidding? Marissa Mayer is no fool. She didn’t take over as Yahoo’s CEO because the company was doing well; she came on board because the stumbling Internet enterprise was an underperforming underachiever that had lost its way.

So when Mayer decrees seven months into the job that she wants people to, you know, physically show up at work instead of telecommuting — or else — I’m pretty confident this reflects a data-driven decision more than a cavalier command. In all likelihood, Mayer has taken good, hard looks at Yahoo’s top 250 performers and top 20 projects and come to her own conclusions about who’s creating real value — and how — in her company. She knows who her best people are.

Let’s be serious: if significant portions of Yahoo top performers were “stay@home” coders, testers and project management telecommuters, do people really think Mayer would arbitrarily issue edicts guaranteed to alienate them? It’s possible. But that would imply Mayer hasn’t learned very much about her company’s best people, best performers and culture since joining last July. Most successful technical leaders I know avoid getting in the way of their best people’s productivity. But what do leaders do when even very good people aren’t being as productive as you want or need them to be? Challenging them to be better onsite collaborators hardly seems either unfair or irrational.

The logical inference to draw from Mayer’s action is that she strongly believes Yahoo’s current “stay@home” telecommuting crowd would be significantly more valuable to the company — organizationally, operationally and culturally — if they came to work. The crueler inference is that both the real and opportunity costs imposed by Yahoo’s “work@homes” greatly exceeded their technical and economic contributions. My bet is that Mayer believes that “working@home” isn’t working for Yahoo — in both meanings of that phrase.

Again, why should this surprise? Flailing companies shouldn’t invest more in what’s not working. The (far) more interesting counterfactual would have been a leaked memo declaring that telecommuters and virtual teams were — by far — the most agile, innovative and productive performers at Yahoo. Therefore the company would delayer its headquarters and remake itself as a virtual networked enterprise. If that had been true, Mayer would have been a different kind of teleworkplace revolutionary.

Then again, Mayer’s Google background (and impact) suggested that she was predisposed to consider physical (co)presence as essential to digital innovation success as computational/design brilliance. After all, one key reason why Google invested so heavily in providing world-class victuals and dining experiences at the Googleplex for its employees wasn’t health food benevolence, it was to keep people on campus working together. Google explicitly encourages and designs for onsite collaboration. Why would Mayer minimize what she had experienced as a critical success factor?

In fairness, critics such as Virgin’s Richard Branson are not wrong when they assert the cultural issues here are arguably as much a matter of trust than facilitating collaboration. But trust cuts both ways. If a CEO authentically concludes that too many “work@homes” have not lived up to their side of the productivity relationship, then the call to return to the workplace could be interpreted as an invitation to rebuild trust. (That’s nicer than simply firing them.)

Culture matters. Ultimately, turnaround CEOs have to make the very public choice around not just how best to empower people but how best to hold them accountable. I take Mayer at her word that she wants to promote the values of “collaborative opportunism” and “opportunistic collaboration” at the “new” Yahoo. That should be a leader’s prerogative. I similarly don’t doubt Mayer knows full well that there’s no shortage of technology enabling high bandwidth, highly functional, high impact collaboration across time zones and zip codes alike. My bet is that, sooner rather than later, the truly productive/high impact employees with special needs will enjoy a locational flexibility that their lesser will not.

But, for the moment, this CEO has done what I always thought good CEOs were supposed to do: identify unproductive “business as usual” practices, declare them unacceptable and incompatible with her cultural aspirations for the firm — and then act. I completely understand why it makes so many employees unhappy. I’m sympathetic to the changes they’re being told to make. But, on this issue for this company, my deeper sympathies belong to the CEO.

To appreciate how broken most contemporary models of advertising and promotion have become, listen to Jeff Bezos complain about how Amazon’s core values are misunderstood. “One of the early examples…was customer reviews,” he recalls. “One [critic] wrote to me and said, ‘You don’t understand your business. You make money when you sell things. Why do you allow these negative customer reviews?’ And when I read that letter, I thought, we don’t make money when we sell things. We make money when we help customers make purchase decisions.”

Exactly. The overwhelming majority of advertising/promotion/marketing/branding investments and expenditures most organizations make today are more about “selling things” than “helping customers.” What do you think customers find more appealing? Amazon invests accordingly. Customers aren’t idiots; they know when they’re being sold. They’re both smart and wired enough to seek out — and appreciate — quality assistance.

Consider Amazon’s recommendation engines. They’re “membrains” interfacing advice and influence: advisory in recommending reasonable and relevant options, influential by basing those options on the choices of people with comparable interests. Bezos’ recommenders are predicated — and dedicated — to the proposition that providing meaningful contexts for customers makes purchasing decisions easier, safer and better. Shoppers are but a click away from learning more about their potential buy. That’s compelling. Recommendation engines and reviews have both proven remarkably (cost)effective sales, marketing and promotional media for Amazon.

The secret of their success, of course, is that they don’t sell. That insight’s neither counter-intuitive nor paradoxical; it reflects the marketplace reality that customers can easily discover everything about your products and services that you don’t want them to — whether it’s true or not. Consequently, the Bezos bet is that relevant recommendations and reviews — good advice — are better brand investments than digital sales pitches. Close the deal by being openly helpful and helpfully open, not by “selling better.” Amazon transformed customer behaviors and expectations by consistently favoring innovative “advice” over sales-oriented “advertising” and promotion. Credibility comes from commitment to facilitate decision, not calculate persuasion.

That’s brand building’s digitally-mediated future. In mobile and tabletized environments, “advertising” increasingly gives way to “advice” and “aducation” — genres that effectively and affectively persuade because they authentically try to do and be more than sales gimmicks. Digital technologies push firms to recognize, rethink and reorganize how they should make their customers smarter and more confident. Turning customers into bargain hunters, after all, doesn’t necessarily make them smarter; it teaches them to pay more attention to the price they pay than to the value they get.

The advice/aducation marketing challenge comes from redefining advertising as an investment that makes your customers more valuable to you, not just an investment that makes your brand more valuable to your customers. Amazon innovatively reinvests with that philosophy and that’s how — and why — it’s successfully redefining retail. Sales don’t drive the UX; they’re its happy byproduct. That digital design sensibility has yet to seep into marketing’s mainstream.

Like retail, advertising and promotion are living through their own version of the showrooming phenomenon. But rather than furtively (or brazenly) price check on one’s mobile in the retail aisle, customers treat typical ads, offers and “calls to action” as yet another piece of data to input into instant search. Precisely because it’s an ad or a coupon, it can’t be trusted. Ironically, that’s digital advertising’s “brand.” Everything worth buying is checkable, Yelpable or Amazonable. Crassly put, advertising becomes less about building brand awareness than triggering digital due diligence.

Where showrooming hollows out traditional retailing’s pricing and promotional strategies, “adzooming” similarly undermines brand narratives and advertising claims. The marketing implications here are infectious, viral and potentially deadly. How receptive will customers, clients and prospects be to hard sell/soft sell advertising and promotions online (and elsewhere) when they’ve been digitally trained and empowered to look for and receive quality recommendations and advice?

The answer to this question is not, “Gee, we need better advertising and promotion!” It’s “organizations need something better than advertising and promotion.”

The distinctions that make a difference will be value-added aducation and advice. After decades of complaints about the poor quality of its instructions and documentation, for example, Ikea set up a YouTube channel showing people how to easily put together its most complex furniture. The “ad”vice and “ad”ucation here is simple and straightforward: the more comfortable and confident Ikea can make its customers about assembling its products, the simpler and easier it becomes for them to make the buy. If you’re marketing, branding and selling Ikea’s brand future, you’ve got to wonder whether “training” and “education” will play marginal or pivotal roles in (re)engaging customers.

Take a quick look at MyLowe’s and P&G’s Pampers sites. They’re nascent — dare I say “baby”? — steps not just to rethink customer engagement, loyalty and “lock-in,” but whether and how to better educate and train customers. Again, information is a necessary but not sufficient condition here. Textbooks — digital or otherwise — are not educators. Who’s going to be the Salman Khan for a Starbucks, a Ford, a Haier and/or a GlaxoSmithKline?

Financial services firms, health care providers, automobile companies and consumer packaged goods enterprises already understand that adding new features and functionality to products and services now matters far less to their branding efforts than figuring out how to get customers to sample and test them. How are you using digital media to help your best customers and prospects to better educate themselves? How are you making them smarter and more capable? Companies like Amazon, Google, Apple, Ikea and IBM have answers to that question. What’s yours?

As fond as brand advertisers may be of talking lizards, doofus dads and hip hamsters behind the wheel, the cutesy and clever is rapidly decaying into memebait. They’ll command attention but little else. The digital and digitizing future belongs to the best aducators and advisors who make clients, customers and prospects measurably smarter and authentically more confident. That’s a challenge a David Ogilvy, Jay Chiat and Rosser Reeves would appreciate. But my bet is their clients will do a better of rising to that challenge than their successors.

The Future of Advertising
An HBR Insight Center

• The Decline and Fall of Product Placement
• Be Funny (But Not Too Funny) In Your Ad Campaign
• Advertisers Should Act More Like Newsrooms
• Advertisers Must Be Inventors

iHave no idea about the iWatch. But iKnow intriguing innovation inspiration when iSee it. The rumored iWatch, much like Apple’s rumored TV, has been a source of frenzied speculation. How might the company that reinvented mobile music, cellular telephony, tablet computing, touchscreen interfaces and downloadable apps reimagine the wristwatch? Just how terrified should Piaget, Rolex and Patek Philippe be?

Very. After all, WWSJD? never really stood for “What Would Steve Jobs Do?”. The acronym really asked, “What would Steve Jobs Design?”. Between its market cap, profit margins and sales volumes, no company has ever done a better job of monetizing great design. Harley Earl and Raymond Loewy could only dream of enjoying the transformative global design influence — technical and experiential — that Apple has exercised this millennium.

Being haunted by the daunting specter of “Apple-ification” has forced many of the firms I know to become far more self-conscious about their design and UX vulnerabilities. “How might an Apple (re)design this?,” has emerged as a rhetorical question that product managers have learned to ask — or be forced to publicly answer.

Similarly, retail and sales organizations squeezed by “showrooming” increasingly wonder, “How would an Amazon (re)design what we’re doing?”. Knowledge-intensive and advice-driven enterprises ask, “What would Google do?”. They’re all smart enough to recognize that these design innovators are setting new standards and expectations for how customers and clients seek out and obtain value.

To my pleasantly provocative surprise, neither fear, loathing nor slavish copycatting dominates the competitive response. While imitation is supposedly the sincerest form of flattery, I’ve enjoyed facilitating wittier and more useful design reactions. Creatively caricaturing one’s competitors turns out to be an insightful, inciteful and empathic way to improve your own.

It began as a joke. At one consumer packaged goods company, the graphic design team humorously despaired that they could never afford to provide a comparable “out of the box” experience for their cheap and perishable product that Apple offered its iPad and Air customers. I agreed but couldn’t help wondering aloud what Apple-fying their package might be like. Two days later, a couple of the designers had mocked up — accent on “mock” — an iPhone/iPod packaging hybrid. It was a tongue-in-cheek caricature that a Sir Jony Ive might have enjoyed (just before calling Apple’s “intellectual property” lawyers.)

By no stretch of the imagination was this intended as a serious design prototype. But it commanded everyone’s attention. The truth was, its Apple-flavored “out of box” experience tasted tangibly different. After fifteen or so minutes of playing around, another designer remarked, “You know, we could….” and it was off to the races. The packaging innovation that ultimately emerged bore no physical resemblance to its parodic origins. However, the focus groups loved it. (The unhappy ending? A senior vice-president did not; he thought the design too much a stretch for the brand.)

With no apologies to Rube Goldberg or Heath Robinson, I quickly embraced the improvisational inspiration of design caricature. Here was a useful, accessible and non-threatening way to literally gain a competitive perspective on design and/or UX challenges. For a B2B web service, I asked the design team to pretend that the site would reside on Amazon. The result was amazing. The exercise completely changed how they thought of integrating recommendations and reviews into the service. Again, the finished product looked nothing like Amazon but the team agreed that the act of emulating the world’s biggest online retailer made them more sensitive to UX and information display trade-offs.

Design parody and caricature has a rich visual history. (I’d credit Giuseppe Arcimboldo as arguably the first and greatest of design caricaturists). Certainly, “starchitects” and uber-designers du jour invariably inspire imitators with either gleams in the eye or evil intent. But most of the (post)industrial design shops I know prefer to “draw inspiration from” rather than actually go through the serious motions of parodic exaggeration of rival designs. The value and cognitive impact comes not from paying attention to the details but from amplifying and exploiting them for effect. Exaggerating the essential design elements ends up revealing fundamental design truths. Making fun of a clever UX style turns out to say something serious about why it’s so appealing.

Professionally, it’s intriguing to observe how designers, who frequently feel challenged to better empathize and sympathize with users, have little trouble at all identifying precisely what features and functions of a rival design they’d most enjoy parodying. They’re relaxed and un-self-conscious. Because they’re actually (re)designing, they’re collaborating instead of just talking. Is design caricature a gimmick? Yes. Does it work? Well, take a good look at your watch and ask yourself: WWSJD?

While discussing a Harvard colleague’s world-class work on how big data and analytics transform public sector effectiveness, I couldn’t help but ask: How many public school systems had reached out to him for advice?

His answer surprised. “I can’t think of any,” he said. “I guess some organizations are more interested in accountability than others.”

Exactly. Enterprise politics and culture suggest analytics’ impact is less about measuring existing performance than creating new accountability. Managements may want to dramatically improve productivity but they’re decidedly mixed about comparably increasing their accountability. Accountability is often the unhappy byproduct rather than desirable outcome of innovative analytics. Greater accountability makes people nervous.

That’s not unreasonable. Look at the vicious politics and debate in New York and other cities over analytics’ role in assessing public school teacher performance. The teachers’ union argues the metrics are an unfair and pseudo-scientific tool to justify firings. Analytics’ champions insist that the transparency and insight these metrics provide are essential for determining classroom quality and outcomes. The arguments over numbers are really fights over accountability and its consequences.

At one global technology services firm, salespeople grew furious with a CRM system whose new analytics effectively held them accountable for pricing and promotion practices they thought undermined their key account relationships. The sophisticated and near-real-time analytics created the worst of both worlds for them: greater accountability with less flexibility and influence.

The evolving marriage of big data to analytics increasingly leads to a phenomenon I’d describe as “accountability creep” — the technocratic counterpart to military “mission creep.” The more data organizations gather from more sources and algorithmically analyze, the more individuals, managers and executives become accountable for any unpleasant surprises and/or inefficiencies that emerge.

For example, an Asia-based supply chain manager can discover that the remarkably inexpensive subassembly he’s successfully procured typically leads to the most complex, time-consuming and expensive in-field repairs. Of course, engineering design and test should be held accountable, but more sophisticated data-driven analytics makes the cost-driven, compliance-oriented supply chain employee culpable, as well.

This helps explain why, when working with organizations implementing big data initiatives and/or analytics, I’ve observed the most serious obstacles tend to have less to do with real quantitative or technical competence than perceived professional vulnerability. The more managements learn about what analytics might mean, the more they fear that the business benefits may be overshadowed by the risk of weakness, dysfunction and incompetence exposed.

Culture matters enormously. Do better analytics lead managers to “improve” or “remove” the measurably underperforming? Are analytics internally marketed and perceived as diagnostics for helping people and processes perform “better”? Or do they identify the productivity pathogens that must quickly and cost-effectively be organizationally excised? What I’ve observed is that many organizations have invested more thought into acquiring analytic capabilities than confronting the accountability crises they may create.

For at least a few organizations, that’s led to “accountability for thee but not for me” investment. Executives use analytics to impose greater accountability upon their subordinates. Analytics become a medium and mechanism for centralizing and consolidating power. Accountability flows up from the bottom; authority flows down from the top.

That’s where resentment arises. The emerging cultural challenge for leadership is whether analytics-driven accountability cuts both ways. Are business unit leaders and top executives using analytics to make themselves more transparent and accountable? Should “accountability analytics” be internally branded as a something “shared” rather than “imposed?”

Transforming the culture and practice of analytics inherently transforms your culture and practice of accountability. The mathematics and technologies of sophisticated analytics are increasingly well understood. The cultures and challenges of accountability are not. Going forward, which do you think will matter more?

Unhappy critics may well look askance at Barack Obama’s performance as Commander-in-Chief. As campaigner-in-chief, however, this President is demonstrably without peer. His “Obama for America” fundraising, analytics and “get out the vote” operation was a masterpiece of agile electoral innovation and entrepreneurship. Partisans from both sides of the aisle believe it transformed presidential politics.

They’re right. But, actually, they’re thinking too small. The Obama campaign’s techniques, tools and technologies deserve detailed and dedicated attention from every organization that takes data-driven decisions seriously. There’s not a brand manager, health care administrator, CMO or CIO who wouldn’t benefit big-time from benchmarking their own operations to this campaign’s. It was that good.

By far the best synthesis and summary of the digital keys to the campaign’s success is Engage DC’s Inside the Cave. I’ve seldom read a briefing so artfully — and accessibly — capturing the critical success factors that turn innovative tools into successful outcomes. Although superbly presented as a case study in campaign organization and technology, its essential lessons go way beyond the mechanics of procuring donors, donations and votes. This is what investing to control your destiny looks like.

The campaign had an outward facing “Digital” component addressing email, social media and fundraising, as well as “Technology” and “Analytics” departments focused on making campaign processes and purchases more efficient. The organization was dedicated to the proposition that it would not just use tools and analytics to get better, it would use them to learn how to get better — and act accordingly. Ego and experience were subordinated to measurable results.

“We basically found our guts were worthless,” observed a senior member of the campaign’s email team, on the fact that nobody on the team could reliably predict which emails would perform best. The campaign committed itself to a relentless regimen of experimentation, test and test again. The team “regularly tested” as many as 18 variations on subject line and email copy. (“Hey” was the most successful subject line of the campaign based on email opens.)

This emphasis on test extended through every phase of the operation. The campaign ran what it called a “Game Day” exercise testing its abilities to respond to possible worst case scenarios of technical failure and surprise. These drills, which coincidentally ran the week before Hurricane Sandy, allowed the DevOps (for Development Operations) team to keep the campaign’s systems running while learning how to perform rapid disaster recovery response.

“We knew what to do,” said Harper Reed, the campaign’s Chief Technology Officer. “We had a runbook that said if this happens, you do this, this and this.” While practice doesn’t necessarily mean perfect, it made a significant difference in organizational and operational effectiveness and esprit. (By painful contrast, the Romney campaign’s experience with its Orca operational system offers a painful case study of what can happen when experimentation and stress-tests are managerially marginalized.)

Whether doing extensive A/B testing on its donation pages or deploying a clever mobile app, “Quick Donate” (which allowed for/facilitated “drunk donating”), the campaign’s technologists and analysts constantly sought to create virtuous cycles of better outcomes leading to better data leading to great efficiencies. I was particularly impressed by how rigorously and relentlessly the analytics teams modeled their “markets,” i.e., the voters and electorate. According to Inside the Cave, the analysts ran 66,000 simulations each night to project who was winning every battleground state, based on dynamic models based on voter contact data. Of course, the analysts were using Facebook and Twitter data, as well.

All these near-real-time “market” data helped determine resource allocation. The campaign developed impressive tools to better optimize the efficiencies and effectiveness of both their digital and traditional media buys. Innovative tools allowed out-of-state volunteers to make calls to swing state undecideds. Indeed, the campaign created a sweet suite of apps and services supporting its “sales force” — i.e., the “get out the vote” volunteers — who would successfully move the needle on election day.

Yes, there were integration problems and issues. Campaign field director Jeremy Bird observed that, “we never got to a point where a field staffer thought it made more sense to text someone than to call them.” But these were frustrations borne of failed effort, not ignorance or intent. I must point out that, even if Obama had lost, the operational innovation and effectiveness of his campaign would still evoke admiration and emulation. No other national campaign has gotten more measurable value from technology, data and analytics in less time than this one.

The briefing’s What’s Next: 2016 is as insightfully useful for today’s CEO as tomorrow’s presidential candidate. Each one of its three big themes — Better Social Targeting, Real Time Analytics Overtakes Polling and True Digital Integration — would likely deserve their own internal task force inside every Fortune 1000 firm.

While it may seem odd to look to a (largely volunteer) presidential campaign for digital/analytical/operational inspiration, (look at Sasha Issenberg’s excellent The Victory Lab for historical context), the fact is that I know of very few business organizations that have gotten comparable value for money and effort from their own innovation investments.

Until the actual “Obama for America” codebase is freely available (and this is the subject of intense debate), if you want a blueprint, map or resource for your own organization’s digital marketing aspirations, read, reread and then circulate Inside the Cave. It will provoke the internal conversation and debate your business likely needs.